Dynamics Learning Rate Bias in Pigeons: Insights from Reinforcement Learning and Neural Correlates

Author:

Jin Fuli12,Yang Lifang12ORCID,Yang Long12,Li Jiajia12,Li Mengmeng12,Shang Zhigang123

Affiliation:

1. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China

2. Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China

3. Institute of Medical Engineering Technology and Data Mining, Zhengzhou University, Zhengzhou 450001, China

Abstract

Research in reinforcement learning indicates that animals respond differently to positive and negative reward prediction errors, which can be calculated by assuming learning rate bias. Many studies have shown that humans and other animals have learning rate bias during learning, but it is unclear whether and how the bias changes throughout the entire learning process. Here, we recorded the behavior data and the local field potentials (LFPs) in the striatum of five pigeons performing a probabilistic learning task. Reinforcement learning models with and without learning rate biases were used to dynamically fit the pigeons’ choice behavior and estimate the option values. Furthemore, the correlation between the striatal LFPs power and the model-estimated option values was explored. We found that the pigeons’ learning rate bias shifted from negative to positive during the learning process, and the striatal Gamma (31 to 80 Hz) power correlated with the option values modulated by dynamic learning rate bias. In conclusion, our results support the hypothesis that pigeons employ a dynamic learning strategy in the learning process from both behavioral and neural aspects, providing valuable insights into reinforcement learning mechanisms of non-human animals.

Funder

National Natural Science Foundation of China

STI 2030-Major Project

National Postdoctoral Researcher Program

Key Scientific and Technological Projects of Henan Province

Publisher

MDPI AG

Subject

General Veterinary,Animal Science and Zoology

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